HistogramNd (ImgLib2 Javadocs 0-SNAPSHOT API)

java.lang.Object
- net.imglib2.histogram.HistogramNd<T>

All Implemented Interfaces:

Iterable<LongType>, Dimensions, EuclideanSpace, Img<LongType>, Interval, IterableInterval<LongType>, IterableRealInterval<LongType>, RandomAccessible<LongType>, RandomAccessibleInterval<LongType>, RealInterval
```
public class HistogramNd<T>
extends Object
implements Img<LongType>
```
A HistogramNd is an n-dimensional histogram that tracks up to four kinds of values: 1) values in the center of the distribution 2) values to the left of the center of the distribution (lower tail) 3) values to the right of the center of the distribution (upper tail) 4) values outside the other areas
Note: the last three classifications may not be present depending upon the makeup of the input data.

Author:

Barry DeZonia

Constructor Summary

Constructors
Constructor and Description
`HistogramNd(HistogramNd<T> other)` Construct a histogram whose bin mappings match another histogram.
`HistogramNd(Iterable<List<T>> data, List<BinMapper1d<T>> mappers)` Construct a histogram from an iterable set of data and a list of bin mapping algorithms.
`HistogramNd(List<BinMapper1d<T>> mappers)` Construct a histogram from a list of bin mapping algorithms.
`HistogramNd(List<Iterable<T>> data, List<BinMapper1d<T>> mappers)` Construct a histogram from an iterable set of data and a list of bin mapping algorithms.

Method Summary

All Methods Instance Methods Concrete Methods
Modifier and Type	Method and Description
`void`	`addData(Iterable<List<T>> data)` Counts additional data contained in a given iterable collection.
`void`	`addData(List<Iterable<T>> data)` Counts additional data contained in a given iterable collection.
`HistogramNd<T>`	`copy()`
`void`	`countData(Iterable<List<T>> data)` Counts the data contained in the given data source using the underlying bin distribution.
`void`	`countData(List<Iterable<T>> data)` Counts the data contained in the given data source using the underlying bin distribution.
`Cursor<LongType>`	`cursor()` Returns a `RealCursor` that iterates with optimal speed without calculating the location at each iteration step.
`void`	`decrement(List<T> values)` Directly decrement a bin by value,
`void`	`decrement(long[] binPos)` Directly decrement a bin by position.
`DiscreteFrequencyDistribution`	`dfd()` Get the discrete frequency distribution associated with this histogram.
`long`	`dimension(int d)` Return the size of the given dimension of the frequency distribution of this histogram.
`void`	`dimensions(long[] dims)` Fill the provided long[] with the sizes of all dimensions of the frequency distribution of this histogram.
`long`	`distributionCount()` Returns the frequency count of all values in the distribution: lower tail + middle + upper tail.
`long`	`distributionCount(int dim, long dimVal)` Returns the frequency count of all values in the specified dimension of the distribution: lower tail + middle + upper tail.
`ImgFactory<LongType>`	`factory()` Get a `ImgFactory` that creates `Img`s of the same kind as this one.
`LongType`	`firstElement()` Get the first element of this `IterableRealInterval`.
`long`	`frequency(List<T> values)` Returns the frequency count of values within a bin using a set of representative values.
`long`	`frequency(long[] binPos)` Returns the frequency count of the values within a bin.
`long`	`getBinCount()` Returns the number of bins contained in the histogram.
`void`	`getCenterValues(long[] binPos, List<T> values)` Gets the values associated with the center of a bin.
`void`	`getLowerBounds(long[] binPos, List<T> values)` Gets the values associated with the left edge of a bin.
`void`	`getUpperBounds(long[] binPos, List<T> values)` Gets the values associated with the right edge of a bin.
`boolean`	`hasTails()` Returns true if the histogram has tail bins which count extreme values for one or more dimensions
`boolean`	`hasTails(int dim)` Returns true if the histogram has tail bins which count extreme values for the given dimension.
`long`	`ignoredCount()` Returns the frequency count of values that were ignored because they could not be mapped to any bin.
`boolean`	`includesLowerBound(int dim, long binPos)` Returns true if the given bin interval is closed on the left for the given dimension.
`boolean`	`includesLowerBounds(long[] binPos)` Returns true if the given bin interval is closed on the left
`boolean`	`includesUpperBound(int dim, long binPos)` Returns true if the given bin interval is closed on the right for the given dimension.
`boolean`	`includesUpperBounds(long[] binPos)` Returns true if the given bin interval is closed on the right
`void`	`increment(List<T> values)` Directly increment a bin by value.
`void`	`increment(long[] binPos)` Directly increment a bin by position.
`boolean`	`isInLowerTail(int dim, T value)` Returns true if a given value for a given dimension is mapped to the lower tail of the distribution.
`boolean`	`isInLowerTail(List<T> values)` Returns true if a given set of values are mapped to the lower tail of the distribution.
`boolean`	`isInMiddle(int dim, T value)` Returns true if a given value for a given dimension is mapped to the middle of the distribution.
`boolean`	`isInMiddle(List<T> values)` Returns true if a given set of values are mapped to the middle of the distribution.
`boolean`	`isInUpperTail(int dim, T value)` Returns true if a given value for a given dimension is mapped to the upper tail of the distribution.
`boolean`	`isInUpperTail(List<T> values)` Returns true if a given set of values are mapped to the upper tail of the distribution.
`boolean`	`isOutside(int dim, T value)` Returns true if a given value for a given dimension is outside the distribution.
`boolean`	`isOutside(List<T> values)` Returns true if a given set of values are outside the distribution.
`Object`	`iterationOrder()` Returns the iteration order of this `IterableRealInterval`.
`Iterator<LongType>`	`iterator()`
`Cursor<LongType>`	`localizingCursor()` Returns a `RealLocalizable` `Iterator` that calculates its location at each iteration step.
`long`	`lowerTailCount()` Returns the frequency count of values in all lower tail bins (if any).
`long`	`lowerTailCount(int dim)` Returns the frequency count of values in the lower tail bin (if any) for the given dimension.
`void`	`map(List<T> values, long[] binPos)` Fills a bin position by mapping from a set of representative values.
`long`	`max(int d)` Get the maximum in dimension d.
`void`	`max(long[] max)` Write the maximum of each dimension into long[].
`void`	`max(Positionable max)` Sets a `Positionable` to the maximum of this `Interval`
`long`	`min(int d)` Get the minimum in dimension d.
`void`	`min(long[] min)` Write the minimum of each dimension into long[].
`void`	`min(Positionable min)` Sets a `Positionable` to the minimum of this `Interval`
`int`	`numDimensions()` Return the number of dimensions of the frequency distribution of this histogram.
`RandomAccess<LongType>`	`randomAccess()` Create a random access sampler for integer coordinates.
`RandomAccess<LongType>`	`randomAccess(Interval interval)` Create a random access sampler for integer coordinates.
`void`	`realMax(double[] max)` Write the maximum of each dimension into double[].
`double`	`realMax(int d)` Default implementation of `RealInterval.realMax(int)`.
`void`	`realMax(RealPositionable max)` Sets a `RealPositionable` to the maximum of this `Interval`
`void`	`realMin(double[] min)` Write the minimum of each dimension into double[].
`double`	`realMin(int d)` Default implementation of `RealInterval.realMin(int)`.
`void`	`realMin(RealPositionable min)` Sets a `RealPositionable` to the minimum of this `Interval`
`double`	`relativeFrequency(List<T> values, boolean includeTails)` Returns the relative frequency of values within a bin using a set of representative values.
`double`	`relativeFrequency(long[] binPos, boolean includeTails)` Returns the relative frequency of values within a bin.
`void`	`resetCounters()` Resets all data counts to 0.
`long`	`size()` Returns the number of elements in this `Function`.
`void`	`subtractData(Iterable<List<T>> data)` Uncounts some original data contained in a given iterable collection.
`void`	`subtractData(List<Iterable<T>> data)` Uncounts some original data contained in a given iterable collection.
`long`	`totalCount()` Returns the total count of all values observed; both within and without the entire distribution.
`long`	`upperTailCount()` Returns the frequency count of values in all upper tail bins (if any).
`long`	`upperTailCount(int dim)` Returns the frequency count of values in the upper tail bin (if any) for the given dimension.
`long`	`valueCount()` Returns the frequency count of all values in the middle of the distribution.
`long`	`valueCount(int dim)` Returns the frequency count of all values in the middle of the distribution for a given dimension.

Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Methods inherited from interface net.imglib2.RandomAccessible
getAt, getAt, getAt

Methods inherited from interface java.lang.Iterable
forEach, spliterator

Methods inherited from interface net.imglib2.Interval
maxAsLongArray, maxAsPoint, minAsLongArray, minAsPoint

Methods inherited from interface net.imglib2.RealInterval
maxAsDoubleArray, maxAsRealPoint, minAsDoubleArray, minAsRealPoint

Methods inherited from interface net.imglib2.Dimensions
allPositive, allPositive, dimensions, dimensionsAsLongArray, dimensionsAsPoint, verify, verify, verifyAllPositive, verifyAllPositive

- Constructor Detail
  - HistogramNd
```
public HistogramNd(List<BinMapper1d<T>> mappers)
```
    Construct a histogram from a list of bin mapping algorithms. Use countData() to populate it.
    
    Parameters:
    
    mappers - The algorithms used to map values to bins
  - HistogramNd
```
public HistogramNd(HistogramNd<T> other)
```
    Construct a histogram whose bin mappings match another histogram. After this construction the histogram bins are unpopulated.
    
    Parameters:
    
    other - The histogram to copy.
  - HistogramNd
```
public HistogramNd(Iterable<List<T>> data,
                   List<BinMapper1d<T>> mappers)
```
    Construct a histogram from an iterable set of data and a list of bin mapping algorithms. Must be given one iterable data source that returns multiple data values at each point.
    
    Parameters:
    
    data - The iterable set of values to calculate upon
    
    mappers - The algorithms used to map values to bins
  - HistogramNd
```
public HistogramNd(List<Iterable<T>> data,
                   List<BinMapper1d<T>> mappers)
```
    Construct a histogram from an iterable set of data and a list of bin mapping algorithms. Must be given multiple iterable data sources that each return a single data value at each point.
    
    Parameters:
    
    data - The iterable set of values to calculate upon
    
    mappers - The algorithms used to map values to bins
- Method Detail
  - hasTails
```
public boolean hasTails(int dim)
```
    Returns true if the histogram has tail bins which count extreme values for the given dimension.
  - hasTails
```
public boolean hasTails()
```
    Returns true if the histogram has tail bins which count extreme values for one or more dimensions
  - lowerTailCount
```
public long lowerTailCount(int dim)
```
    Returns the frequency count of values in the lower tail bin (if any) for the given dimension.
  - lowerTailCount
```
public long lowerTailCount()
```
    Returns the frequency count of values in all lower tail bins (if any).
  - upperTailCount
```
public long upperTailCount(int dim)
```
    Returns the frequency count of values in the upper tail bin (if any) for the given dimension.
  - upperTailCount
```
public long upperTailCount()
```
    Returns the frequency count of values in all upper tail bins (if any).
  - valueCount
```
public long valueCount(int dim)
```
    Returns the frequency count of all values in the middle of the distribution for a given dimension.
  - valueCount
```
public long valueCount()
```
    Returns the frequency count of all values in the middle of the distribution.
  - distributionCount
```
public long distributionCount(int dim,
                              long dimVal)
```
    Returns the frequency count of all values in the specified dimension of the distribution: lower tail + middle + upper tail. Does not include ignored values.
  - distributionCount
```
public long distributionCount()
```
    Returns the frequency count of all values in the distribution: lower tail + middle + upper tail. Does not include ignored values.
  - ignoredCount
```
public long ignoredCount()
```
    Returns the frequency count of values that were ignored because they could not be mapped to any bin.
  - totalCount
```
public long totalCount()
```
    Returns the total count of all values observed; both within and without the entire distribution. Thus it includes ignored values. One should decide carefully between using distributionCount() and totalCount().
  - frequency
```
public long frequency(List<T> values)
```
    Returns the frequency count of values within a bin using a set of representative values. Note that multiple values can be mapped to one bin so this is NOT the frequency count of this exact set of values in the distribution.
    
    Parameters:
    
    values - A set of representative values of interest
  - frequency
```
public long frequency(long[] binPos)
```
    Returns the frequency count of the values within a bin.
  - relativeFrequency
```
public double relativeFrequency(List<T> values,
                                boolean includeTails)
```
    Returns the relative frequency of values within a bin using a set of representative values. Note that multiple values can be mapped to one bin so this is NOT the relative frequency of this exact set of values in the distribution.
    This calculation is of the number of values in the bin divided by either the number of values in the distribution or the number of values in the center of the distribution (tails ignored).
    One can devise other ways to count relative frequencies that consider ignored values also. If needed one can use the various count methods and frequency methods to calculate any relative frequency desired.
    
    Parameters:
    
    values - A representative set of values of interest
    
    includeTails - Flag for determining whether to include tails in calculation.
  - relativeFrequency
```
public double relativeFrequency(long[] binPos,
                                boolean includeTails)
```
    Returns the relative frequency of values within a bin.
    This calculation is of the number of values in the bin divided by either the number of values in the distribution or the number of values in the center of the distribution (tails ignored).
    One can devise other ways to count relative frequencies that consider ignored values also. If needed one can use the various count methods and frequency methods to calculate any relative frequency desired.
    
    Parameters:
    
    binPos - The position of the bin of interest
    
    includeTails - Flag for determining whether to include tails in calculation.
  - getBinCount
```
public long getBinCount()
```
    Returns the number of bins contained in the histogram.
  - map
```
public void map(List<T> values,
                long[] binPos)
```
    Fills a bin position by mapping from a set of representative values.
  - getCenterValues
```
public void getCenterValues(long[] binPos,
                            List<T> values)
```
    Gets the values associated with the center of a bin.
    
    Parameters:
    
    binPos - The bin index of interest
    
    values - The outputs to fill with the center values
  - getLowerBounds
```
public void getLowerBounds(long[] binPos,
                           List<T> values)
```
    Gets the values associated with the left edge of a bin.
    
    Parameters:
    
    binPos - The bin index of interest
    
    values - The outputs to fill with the left edge values
  - getUpperBounds
```
public void getUpperBounds(long[] binPos,
                           List<T> values)
```
    Gets the values associated with the right edge of a bin.
    
    Parameters:
    
    binPos - The bin index of interest
    
    values - The outputs to fill with the right edge values
  - includesUpperBounds
```
public boolean includesUpperBounds(long[] binPos)
```
    Returns true if the given bin interval is closed on the right
    
    Parameters:
    
    binPos - The bin number of the interval of interest
  - includesLowerBounds
```
public boolean includesLowerBounds(long[] binPos)
```
    Returns true if the given bin interval is closed on the left
    
    Parameters:
    
    binPos - The bin number of the interval of interest
  - includesUpperBound
```
public boolean includesUpperBound(int dim,
                                  long binPos)
```
    Returns true if the given bin interval is closed on the right for the given dimension.
    
    Parameters:
    
    dim - The dimension of interest
    
    binPos - The bin number of the interval of interest
  - includesLowerBound
```
public boolean includesLowerBound(int dim,
                                  long binPos)
```
    Returns true if the given bin interval is closed on the left for the given dimension.
    
    Parameters:
    
    dim - The dimension of interest
    
    binPos - The bin number of the interval of interest
  - isInLowerTail
```
public boolean isInLowerTail(List<T> values)
```
    Returns true if a given set of values are mapped to the lower tail of the distribution.
    
    Parameters:
    
    values - The set of values to determine the location of
  - isInLowerTail
```
public boolean isInLowerTail(int dim,
                             T value)
```
    Returns true if a given value for a given dimension is mapped to the lower tail of the distribution.
    
    Parameters:
    
    dim - The dimension number of the axis of interest
    
    value - The value to determine the location of
  - isInUpperTail
```
public boolean isInUpperTail(List<T> values)
```
    Returns true if a given set of values are mapped to the upper tail of the distribution.
    
    Parameters:
    
    values - The set of values to determine the location of
  - isInUpperTail
```
public boolean isInUpperTail(int dim,
                             T value)
```
    Returns true if a given value for a given dimension is mapped to the upper tail of the distribution.
    
    Parameters:
    
    dim - The dimension number of the axis of interest
    
    value - The value to determine the location of
  - isInMiddle
```
public boolean isInMiddle(List<T> values)
```
    Returns true if a given set of values are mapped to the middle of the distribution.
    
    Parameters:
    
    values - The set of values to determine the location of
  - isInMiddle
```
public boolean isInMiddle(int dim,
                          T value)
```
    Returns true if a given value for a given dimension is mapped to the middle of the distribution.
    
    Parameters:
    
    dim - The dimension number of the axis of interest
    
    value - The value to determine the location of
  - isOutside
```
public boolean isOutside(List<T> values)
```
    Returns true if a given set of values are outside the distribution.
    
    Parameters:
    
    values - The set of values to determine the location of
  - isOutside
```
public boolean isOutside(int dim,
                         T value)
```
    Returns true if a given value for a given dimension is outside the distribution.
    
    Parameters:
    
    value - The value to determine the location of
  - dfd
```
public DiscreteFrequencyDistribution dfd()
```
    Get the discrete frequency distribution associated with this histogram.
  - countData
```
public void countData(Iterable<List<T>> data)
```
    Counts the data contained in the given data source using the underlying bin distribution.
    
    Parameters:
    
    data - The total data to count
  - countData
```
public void countData(List<Iterable<T>> data)
```
    Counts the data contained in the given data source using the underlying bin distribution.
    
    Parameters:
    
    data - The total data to count
  - addData
```
public void addData(Iterable<List<T>> data)
```
    Counts additional data contained in a given iterable collection. One can use this to update an existing histogram with a subset of values.
    
    Parameters:
    
    data - The new data to count
  - addData
```
public void addData(List<Iterable<T>> data)
```
    Counts additional data contained in a given iterable collection. One can use this to update an existing histogram with a subset of values.
    
    Parameters:
    
    data - The new data to count
  - subtractData
```
public void subtractData(Iterable<List<T>> data)
```
    Uncounts some original data contained in a given iterable collection. One can use this to update an existing histogram with a subset of values.
    
    Parameters:
    
    data - The old data to uncount
  - subtractData
```
public void subtractData(List<Iterable<T>> data)
```
    Uncounts some original data contained in a given iterable collection. One can use this to update an existing histogram with a subset of values.
    
    Parameters:
    
    data - The old data to uncount
  - increment
```
public void increment(long[] binPos)
```
    Directly increment a bin by position.
    
    Parameters:
    
    binPos - The 1-d index of the bin
  - decrement
```
public void decrement(long[] binPos)
```
    Directly decrement a bin by position.
    
    Parameters:
    
    binPos - The 1-d index of the bin
  - increment
```
public void increment(List<T> values)
```
    Directly increment a bin by value.
    
    Parameters:
    
    values - The values to map to a bin position
  - decrement
```
public void decrement(List<T> values)
```
    Directly decrement a bin by value,
    
    Parameters:
    
    values - The values to map to a bin position
  - resetCounters
```
public void resetCounters()
```
    Resets all data counts to 0.
  - numDimensions
```
public int numDimensions()
```
    Return the number of dimensions of the frequency distribution of this histogram.
    
    Specified by:
    
    numDimensions in interface EuclideanSpace
  - dimension
```
public long dimension(int d)
```
    Return the size of the given dimension of the frequency distribution of this histogram.
    
    Specified by:
    
    dimension in interface Dimensions
    
    Specified by:
    
    dimension in interface Interval
  - dimensions
```
public void dimensions(long[] dims)
```
    Fill the provided long[] with the sizes of all dimensions of the frequency distribution of this histogram.
    
    Specified by:
    
    dimensions in interface Dimensions
  - randomAccess
```
public RandomAccess<LongType> randomAccess()
```
    Description copied from interface: RandomAccessible
    Create a random access sampler for integer coordinates.
    The returned random access covers as much of the domain as possible.
    Please note: RandomAccessibleIntervals have a finite domain (their Interval), so RandomAccessible.randomAccess() is only guaranteed to cover this finite domain. This may lead to unexpected results when using Views. In the following code
```
 RandomAccessible<T> extended = Views.extendBorder( img )
 RandomAccessibleInterval<T> cropped = Views.interval( extended, img );
 RandomAccess<T> a1 = extended.randomAccess();
 RandomAccess<T> a2 = cropped.randomAccess();
 
```
    The access a1 on the extended image is valid everywhere. However, somewhat counter-intuitively, the access a2 on the extended and cropped image is only valid on the interval img to which the extended image was cropped. The access is only required to cover this interval, because it is the domain of the cropped image. Views attempts to provide the fastest possible access that meets this requirement, and will therefore strip the extension. To deal with this, if you know that you need to access pixels outside the domain of the RandomAccessibleInterval, and you know that the RandomAccessibleInterval is actually defined beyond its interval boundaries, then use the RandomAccessible.randomAccess(Interval) variant and specify which interval you actually want to access. In the above example,
```
 RandomAccess<T> a2 = cropped.randomAccess( Intervals.expand( img, 10 ) );
 
```
    will provide the extended access as expected.
    Specified by:
    
    randomAccess in interface RandomAccessible<LongType>
    
    Returns:
    
    random access sampler
  - randomAccess
```
public RandomAccess<LongType> randomAccess(Interval interval)
```
    Description copied from interface: RandomAccessible
    
    Create a random access sampler for integer coordinates.
    The returned random access is intended to be used in the specified interval only. Thus, the RandomAccessible may provide optimized versions. If the interval is completely contained in the domain, the random access is guaranteed to provide the same values as that obtained by RandomAccessible.randomAccess() within the interval.
    
    Specified by:
    
    randomAccess in interface RandomAccessible<LongType>
    
    Parameters:
    
    interval - in which interval you intend to use the random access.
    
    Returns:
    
    random access sampler
  - min
```
public long min(int d)
```
    Description copied from interface: Interval
    
    Get the minimum in dimension d.
    
    Specified by:
    
    min in interface Interval
    
    Parameters:
    
    d - dimension
    
    Returns:
    
    minimum in dimension d.
  - min
```
public void min(long[] min)
```
    Description copied from interface: Interval
    
    Write the minimum of each dimension into long[].
    
    Specified by:
    
    min in interface Interval
  - min
```
public void min(Positionable min)
```
    Description copied from interface: Interval
    
    Sets a Positionable to the minimum of this Interval
    
    Specified by:
    
    min in interface Interval
  - max
```
public long max(int d)
```
    Description copied from interface: Interval
    
    Get the maximum in dimension d.
    
    Specified by:
    
    max in interface Interval
    
    Parameters:
    
    d - dimension
    
    Returns:
    
    maximum in dimension d.
  - max
```
public void max(long[] max)
```
    Description copied from interface: Interval
    
    Write the maximum of each dimension into long[].
    
    Specified by:
    
    max in interface Interval
  - max
```
public void max(Positionable max)
```
    Description copied from interface: Interval
    
    Sets a Positionable to the maximum of this Interval
    
    Specified by:
    
    max in interface Interval
  - realMin
```
public double realMin(int d)
```
    Description copied from interface: Interval
    
    Default implementation of RealInterval.realMin(int).
    
    Specified by:
    
    realMin in interface Interval
    
    Specified by:
    
    realMin in interface RealInterval
    
    Parameters:
    
    d - dimension
    
    Returns:
    
    minimum in dimension d.
  - realMin
```
public void realMin(double[] min)
```
    Description copied from interface: RealInterval
    
    Write the minimum of each dimension into double[].
    
    Specified by:
    
    realMin in interface RealInterval
  - realMin
```
public void realMin(RealPositionable min)
```
    Description copied from interface: RealInterval
    
    Sets a RealPositionable to the minimum of this Interval
    
    Specified by:
    
    realMin in interface RealInterval
  - realMax
```
public double realMax(int d)
```
    Description copied from interface: Interval
    
    Default implementation of RealInterval.realMax(int).
    
    Specified by:
    
    realMax in interface Interval
    
    Specified by:
    
    realMax in interface RealInterval
    
    Parameters:
    
    d - dimension
    
    Returns:
    
    maximum in dimension d.
  - realMax
```
public void realMax(double[] max)
```
    Description copied from interface: RealInterval
    
    Write the maximum of each dimension into double[].
    
    Specified by:
    
    realMax in interface RealInterval
  - realMax
```
public void realMax(RealPositionable max)
```
    Description copied from interface: RealInterval
    
    Sets a RealPositionable to the maximum of this Interval
    
    Specified by:
    
    realMax in interface RealInterval
  - cursor
```
public Cursor<LongType> cursor()
```
    Description copied from interface: IterableRealInterval
    
    Returns a RealCursor that iterates with optimal speed without calculating the location at each iteration step. Localization is performed on demand.
    
    Use this where localization is required rarely/ not for each iteration.
    
    Specified by:
    
    cursor in interface IterableInterval<LongType>
    
    Specified by:
    
    cursor in interface IterableRealInterval<LongType>
    
    Returns:
    
    fast iterating iterator
  - localizingCursor
```
public Cursor<LongType> localizingCursor()
```
    Description copied from interface: IterableRealInterval
    
    Returns a RealLocalizable Iterator that calculates its location at each iteration step. That is, localization is performed with optimal speed.
    
    Use this where localization is required often/ for each iteration.
    
    Specified by:
    
    localizingCursor in interface IterableInterval<LongType>
    
    Specified by:
    
    localizingCursor in interface IterableRealInterval<LongType>
    
    Returns:
    
    fast localizing iterator
  - size
```
public long size()
```
    Description copied from interface: IterableRealInterval
    
    Returns the number of elements in this Function.
    
    Specified by:
    
    size in interface IterableRealInterval<LongType>
    
    Returns:
    
    number of elements
  - firstElement
```
public LongType firstElement()
```
    Description copied from interface: IterableRealInterval
    
    Get the first element of this IterableRealInterval. This is a shortcut for cursor().next(). This can be used to create a new variable of type T using firstElement().createVariable(), which is useful in generic methods to store temporary results, e.g., a running sum over pixels in the IterableRealInterval.
    
    Specified by:
    
    firstElement in interface IterableRealInterval<LongType>
    
    Returns:
    
    the first element in iteration order.
  - iterationOrder
```
public Object iterationOrder()
```
    Description copied from interface: IterableRealInterval
    
    Returns the iteration order of this IterableRealInterval. If the returned object equals (Object.equals(Object)) the iteration order of another IterableRealInterval f then they can be copied by synchronous iteration. That is, having an Iterator on this and another Iterator on f, moving both in synchrony will point both of them to corresponding locations in their source domain. In other words, this and f have the same iteration order and means and the same number of elements.
    
    Specified by:
    
    iterationOrder in interface IterableRealInterval<LongType>
    
    Returns:
    
    the iteration order of this IterableRealInterval.
    
    See Also:
    
    FlatIterationOrder
  - iterator
```
public Iterator<LongType> iterator()
```
    Specified by:
    
    iterator in interface Iterable<LongType>
  - factory
```
public ImgFactory<LongType> factory()
```
    Description copied from interface: Img
    
    Get a ImgFactory that creates Imgs of the same kind as this one. This is useful to create Imgs for temporary storage in generic methods where the specific Img type is unknown. Note, that the factory can be used even if all references to this Img have been invalidated.
    
    Specified by:
    
    factory in interface Img<LongType>
    
    Returns:
    
    a factory for Imgs of the same kind as this one.
  - copy
```
public HistogramNd<T> copy()
```
    Specified by:
    
    copy in interface Img<LongType>
    
    Returns:
    
    - A copy of the current Img instance, all pixels are duplicated

Class HistogramNd<T>

Constructor Summary

Method Summary

Methods inherited from class java.lang.Object

Methods inherited from interface net.imglib2.RandomAccessible

Methods inherited from interface java.lang.Iterable

Methods inherited from interface net.imglib2.Interval

Methods inherited from interface net.imglib2.RealInterval

Methods inherited from interface net.imglib2.Dimensions

Constructor Detail

HistogramNd

HistogramNd

HistogramNd

HistogramNd

Method Detail

hasTails

hasTails

lowerTailCount

lowerTailCount

upperTailCount

upperTailCount

valueCount

valueCount

distributionCount

distributionCount

ignoredCount

totalCount

frequency

frequency

relativeFrequency

relativeFrequency

getBinCount

map

getCenterValues

getLowerBounds

getUpperBounds

includesUpperBounds

includesLowerBounds

includesUpperBound

includesLowerBound

isInLowerTail

isInLowerTail

isInUpperTail

isInUpperTail

isInMiddle

isInMiddle

isOutside

isOutside

dfd

countData

countData

addData

addData

subtractData

subtractData

increment

decrement

increment

decrement

resetCounters

numDimensions

dimension

dimensions

randomAccess

randomAccess

min

min

min

max

max

max

realMin

realMin

realMin

realMax

realMax

realMax

cursor

localizingCursor

size